Motion-based kinetic fingerprint radio selection

ABSTRACT

Motion adaptive wireless user equipment (UE) in a wireless network are provided. Kinetic information is leveraged to select a preferred radio (or radio technology) or adapt a reselection scanning interval. This can serve to improve the performance of a UE by reducing the amount of power expended in maintaining an adequate level of connectedness to the wireless network components in the face of UE movement. In a further aspect, kinetic power generators can be employed as a source of UE transit data. Kinetic fingerprints can be compared to UE transit data, e.g., that acquired from a kinetic generator of the UE, to facilitate selection of preferred radios and reselection intervals. In this aspect, radio selection schema and reselection scanning schema can effectively be selected with little to no drain on a UE power source.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.12/946,611, filed Nov. 15, 2010 and titled “RADIO SELECTION EMPLOYINGTRANSIT DATA DETERMINED FROM KINETIC ENERGY GENERATION”, the entirety ofwhich is hereby incorporated by reference.

TECHNICAL FIELD

The present application relates generally to wireless communicationsnetworks, and more particularly, to motion adaptive user equipment (UE)in a wireless communications network environment for selecting a radiotechnology of the UE and/or scheduling reselection scanning performed bythe UE.

BACKGROUND

In wireless communications networks, modern wireless communicationdevices, e.g., user equipment (UE), support more frequency bands andtechnologies than ever before. In order to benefit from this availablenetwork bandwidth and capacity, each device must be aware of what isavailable while camping and/or before voice or data calls or othercommunication transactions are made. In complex multi-technology andfrequency band scenarios, associated UE may scan, for example, severaldifferent technologies across multiple different frequency bands, whichcan be beneficial. Moreover, lacking proactive information aboutavailable networks, smart network selection techniques can be slowed orbe less functional.

According to traditional network scanning techniques, devicesperiodically scan various frequency bands and technologies. A preferredfrequency and radio technology can then be selected and camped on by adevice. Such scanning typically requires receiver and battery resourceswhile the UE is otherwise idle. If scanning is too frequent, batterystandby time can be reduced. On the other hand, if scanning is tooinfrequent, the UE can lack an appropriate level of awareness of thesurrounding networks and can thus make inappropriate selectiondecisions. Either result is generally undesirable.

The above-described deficiencies of today's wireless communicationstechnologies are merely intended to provide an overview of some of theproblems of conventional systems, and are not intended to be exhaustive.Other problems with conventional systems and corresponding benefits ofthe various non-limiting embodiments described herein may become furtherapparent upon review of the following description.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating a system that can facilitatemotion adaptive user equipment selection of at least a radio technologyor a reselection interval in accordance with aspects of the disclosedsubject matter.

FIG. 2 is a block diagram of a system employing a kinetic fingerprint toselect at least a radio technology or a reselection interval inaccordance with aspects of the disclosed subject matter.

FIG. 2 b is a block diagram of a system employing a kinetic fingerprintto select at least a radio technology or a reselection interval inaccordance with aspects of the disclosed subject matter.

FIG. 3 is a block diagram of a system for motion adaptive user equipmentemploying a kinetic sensor in accordance with aspects described herein.

FIG. 4 is a block diagram of a system for motion adaptive user equipmentemploying a kinetic generator in accordance with aspects describedherein.

FIG. 5 is a block diagram of a system for motion adaptive user equipmentemploying frequency analysis technology in accordance with aspectsdescribed herein.

FIG. 6 is a block diagram of a system for motion adaptive user equipmentemploying learning technology in accordance with aspects describedherein.

FIG. 7 is an exemplary flowchart of procedures defining a method fordetermining at least a preferential radio technology parameter orreselection interval parameter in accordance with aspects describedherein.

FIG. 8 is an exemplary flowchart of procedures defining a method fordetermining at least a preferential radio technology parameter orreselection interval parameter in accordance with aspects describedherein.

FIG. 9 is an exemplary flowchart of procedures defining a method fordetermining at least a preferential radio technology parameter orreselection interval parameter in accordance with aspects describedherein.

FIG. 10 illustrates an exemplary wireless communications environmentwith associated components that can enable operation of an enterprisenetwork in accordance with aspects of the disclosed subject matter.

FIG. 11 illustrates a schematic deployment of a macro cell for wirelesscoverage in accordance with aspects of the subject specification.

FIG. 12 illustrates a block diagram of a computer operable to execute aportion of the disclosed architecture.

DETAILED DESCRIPTION

The disclosed subject matter is now described with reference to thedrawings, wherein like reference numerals are used to refer to likeelements throughout. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providea thorough understanding of the disclosed subject matter. It may beevident, however, that the disclosed subject matter may be practicedwithout these specific details. In other instances, well-knownstructures and devices are shown in block diagram form in order tofacilitate describing the disclosed subject matter.

One or more embodiments of the disclosed subject matter analyze userequipment (UE) transit data. In a non-limiting aspect of the disclosedsubject matter, UE transit data can be analyzed to determine radioselection information. Radio selection information can be related topreferential enablement or preferential disablement of one or more UEradios or radio technologies of the UE. For example, this can allow awireless radio, e.g., an IEEE 802.xx radio (WiFi), etc., to be turnedoff and a Bluetooth radio to be turned on based on the movement of thehost UE.

In another non-limiting aspect, UE transit data can be analyzed to aidin the defining reselection scanning schedules by providing reselectioninterval information related to preferential rescanning intervals. Thiscan supplement or replace reselection scanning schedules generated byother means. This can be beneficial where, for example, the granularityof other methods may not be sufficient to provide relevant intervalscheduling.

In a further non-limiting aspect, kinetic power generators can beemployed as a source of UE transit data. Where a kinetic generatortypically generates power when moved, the generator output can beclosely correlated to motion. As such, UEs having kinetic generators canemploy the output of a kinetic generator as a source of UE transit data.This can be beneficial where the kinetic generator also provides powerto the UE because radio selection and/or reselection scanning schema canbe accomplished with little to no negative effect on UE resources, e.g.,battery life.

Aspects, features, or advantages of the various embodiments of thesubject disclosure can be exploited in wireless telecommunicationdevices, systems or networks. Non-limiting examples of such devices ornetworks include Femto-cell technology, Wi-Fi, e.g., various 802.xxtechnologies, etc., Worldwide Interoperability for Microwave Access(WiMAX); Enhanced General Packet Radio Service (Enhanced GPRS); ThirdGeneration Partnership Project (3GPP) Long Term Evolution (LTE); 3GPPUniversal Mobile Telecommunications System (UMTS); Third GenerationPartnership Project 2 (3GPP2) Ultra Mobile Broadband (UMB); High SpeedPacket Access (HSPA); High Speed Downlink Packet Access (HSDPA); HighSpeed Uplink Packet Access (HSUPA); GSM Enhanced Data Rate for GSMEvolution (EDGE) Radio Access Network (RAN) or GERAN; UMTS TerrestrialRadio Access Network (UTRAN); LTE Advanced, femtocell(s), microcell(s),Bluetooth, etc. Additionally, aspects of the disclosed subject mattercan include legacy telecommunication technologies.

As used in this application, the terms “component,” “system,”“platform,” “layer,” “selector,” “interface,” and the like are intendedto refer to a computer-related entity or an entity related to anoperational apparatus with one or more specific functionalities, whereinthe entity can be either hardware, a combination of hardware andsoftware, software, or software in execution. As an example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution, a program,and/or a computer. By way of illustration, both an application runningon a server and the server can be a component. One or more componentsmay reside within a process and/or thread of execution and a componentmay be localized on one computer and/or distributed between two or morecomputers. Also, these components can execute from various computerreadable media having various data structures stored thereon. Thecomponents may communicate via local and/or remote processes such as inaccordance with a signal having one or more data packets, e.g., datafrom one component interacting with another component in a local system,distributed system, and/or across a network such as the Internet withother systems via the signal. As another example, a component can be anapparatus with specific functionality provided by mechanical partsoperated by electric or electronic circuitry, which is operated by asoftware or firmware application executed by a processor, wherein theprocessor can be internal or external to the apparatus and executes atleast a part of the software or firmware application. As yet anotherexample, a component can be an apparatus that provides specificfunctionality through electronic components without mechanical parts,the electronic components can include a processor therein to executesoftware or firmware that confers at least in part the functionality ofthe electronic components.

Moreover, the word “exemplary” is used herein to mean serving as anexample, instance, or illustration. Any aspect or design describedherein as “exemplary” is not necessarily to be construed as preferred oradvantageous over other aspects or designs. Rather, use of the wordexemplary is intended to present concepts in a concrete fashion.

In addition, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom context, “X employs A or B” is intended to mean any of the naturalinclusive permutations. That is, if X employs A; X employs B; or Xemploys both A and B, then “X employs A or B” is satisfied under any ofthe foregoing instances. Moreover, articles “a” and “an” as used in thesubject specification and annexed drawings should generally be construedto mean “one or more” unless specified otherwise or clear from contextto be directed to a singular form.

Moreover, terms like “user equipment (UE),” “mobile station,” “mobile,”subscriber station,” “subscriber equipment,” “access terminal,”“terminal,” “handset,” and similar terminology, refer to a wirelessdevice utilized by a subscriber or user of a wireless communicationservice to receive or convey data, control, voice, video, sound, gaming,or substantially any data-stream or signaling-stream. The foregoingterms are utilized interchangeably in the subject specification andrelated drawings. Likewise, the terms “access point (AP),” “basestation,” “Node B,” “evolved Node B (eNode B),” “home Node B (HNB),”“home access point (HAP),” and the like, are utilized interchangeably inthe subject application, and refer to a wireless network component orappliance that serves and receives data, control, voice, video, sound,gaming, or substantially any data-stream or signaling-stream from a setof subscriber stations. Data and signaling streams can be packetized orframe-based flows.

Furthermore, the terms “user,” “subscriber,” “customer,” “consumer,”“prosumer,” “agent,” and the like are employed interchangeablythroughout the subject specification, unless context warrants particulardistinction(s) among the terms. It should be appreciated that such termscan refer to human entities or automated components supported throughartificial intelligence, e.g., a capacity to make inference based oncomplex mathematical formalisms, which can provide simulated vision,sound recognition and so forth.

As used herein, the terms “infer” or “inference” generally refer to theprocess of reasoning about or inferring states of the system,environment, and/or user from a set of observations as captured viaevents and/or data. Inference can be employed to identify a specificcontext or action, or can generate a probability distribution overstates, for example. The inference can be probabilistic—that is, thecomputation of a probability distribution over states of interest basedon a consideration of data and events. Inference can also refer totechniques employed for composing higher-level events from a set ofevents and/or data. Such inference results in the construction of newevents or actions from a set of observed events and/or stored eventdata, whether or not the events are correlated in close temporalproximity, and whether the events and data come from one or severalevent and data sources.

FIG. 1 is a block diagram illustrating a system 100 that can facilitatemotion adaptive user equipment (UE) selection of at least a radiotechnology or a reselection interval in accordance with aspects of thedisclosed subject matter. As disclosed in related application (U.S. Ser.No. 12/624,643), incorporated herein in the entirety by reference, anarchitecture can determine a scanning schedule for reselection scanningin connection with a wireless communication network or service, e.g., bytracking UE movement between nodeB locations in a given time interval.These measurements can be employed to calculate a reselection scanningschedule based in part on the UE speed (or lack thereof) throughwireless communication network resources. In accordance therewith, theforegoing architecture can include a mobility component that candetermine a current mobility pattern for UE, e.g., a change in locationfor the UE or a speed or velocity for the UE. The mobility pattern canbe constructed based upon an examination of a history of cell IDsselected by the UE during recent reselection scans, which can indicateor be representative of UE movement as well as the pattern of movement.In addition, the foregoing architecture can include an assignmentcomponent that can determine a reselection scanning schedule for the UEbased upon the mobility pattern. In an aspect this can facilitateextended battery life due to fewer reselection scans performed by the UEwhere said scans are more likely to be redundant, e.g., where there islittle or no mobility of the UE.

System 100 illustrates a related system that can employ UE transit datato facilitate selection of reselection interval (which can be consideredin determining a reselection scanning schedule as disclosed in relatedapplication (U.S. Ser. No. 12/624,643) as disclosed supra) as well asfor selecting an radio technology. It is becoming more common for UEs toinclude multiple radios and/or radio technologies, e.g., radios forCDMA, TDMA, WiFi, Bluetooth, etc., which can be independently controlledto effect communication or data transfer with between the UE and variouselements of one or more wireless communications networks. As anon-limiting example, a smartphone can have both a WiFi radio and acellular radio such that the WiFi radio can be used exclusive of thecellular radio (or vice versa) to effect communications, e.g., email canbe accessed over either the cellular or WiFi radios. As each specificradio and/or radio technology may perform better (or worse) than acompeting technology for a given set of conditions, selection of theradio/radio technology can afford an improved user experience. Forexample, where a user is relatively stationary in their office, WiFi canbe preferential to a cellular radio, e.g., greater bandwidth, moreavailable resources, lower power consumption, etc., while, in contrast,when a user is moving rapidly down a freeway, e.g., in a bus or taxi, acellular connection can be preferential, e.g., rapid transitions acrossa plurality of WiFi resources is generally resource intensive ascompared to the longer period of residence afforded by a nodeB.

Whereas system 100 facilitates the selection of radios/radiotechnologies, an improved user experience can be achieved. System 100can include transit analysis component (TAC) 110 to analyze UE transitdata to facilitate selection of a radio (or radio technology) and/or areselection interval. For example, where a user is moving rapidly in atrain, TAC 110 can determine that the user is moving rapidly and thatthere is a frequency component to the movement that is associated withtrain travel, e.g., there is a frequency to the movement of the UE thatcan come from the train crossing track welds, acceleration/decelerationof a train from/into a station, swaying of a train car during transit,etc. Where train travel is a possibility, TAC 110 can, for example,indicate that an initial scan for a train-car-WiFi connection be madeand, where no WiFi is detected, can indicate that the WiFi radio shouldbe powered down to conserve battery life. Further, in the example, TAC110 can also indicate that the cellular radio remain on subject to areselection scanning schedule appropriate for train speed movement (orin conjunction with the subject matter for determining a reselectionscan as disclosed in related application (U.S. Ser. No. 12/624,643)).

TAC 110 can analyze UE transit data to form a kinetic fingerprint thatcan be applied in radio selection models to aid in the selection ofpreferential radios or radio technologies. Further, this kineticfingerprint can contribute to improved determination of reselectionscanning schedules. A kinetic fingerprint can be based on data relatedto the transit of UEs. As such, a kinetic fingerprint can be based on awide variety of motion data sources, for example, GPS data,accelerometers, and of course speed calculations between nodeBs forgiven time intervals. However, each of these data sources generally isassociated with further taxing of UE resources. For example, a GPSgenerally is considered to consume a significant amount of UE power thatcan rapidly discharge modern UE battery technologies. As such, using GPScan be undesirable. Further, for example, GPS can function poorly insidestructures and thus make it undesirable for use in computing radiotechnology selection and reselection scanning intervals. In an aspect,TAC 110 can be communicatively coupled to a kinetic generator (notillustrated) to provide UE transit data. Further, a kinetic generatorcan provide UE transit data with minimal depletion of UE resources,e.g., with little or no net battery drain from UE transit dataacquisition.

FIG. 2 is a block diagram of a system 200 employing a kineticfingerprint to select at least a radio technology or a reselectioninterval in accordance with aspects of the disclosed subject matter.System 200 can include TAC 210. TAC 210 can be the same as, or similarto, TAC 110. TAC 210 can access UE transit data as disclosed hereinabove. TAC 210 can include kinetic fingerprint component 220. Kineticfingerprint component 230 can be employed to determine close matches (orperfect matches) between known (or inferred) UE kinetic patterns andaccessed UE transit patterns. Kinetic fingerprint matches can be any UEtransit pattern criterion (criteria) that transitions a predeterminedcriterion (criteria) associated with one or more predetermined UEkinetic patterns. As a non-limiting example, where a UE kinetic patternfor a UE kinetic generator is predetermined to have a regular sinusoidalpattern of power generation with a frequency between 0.5 and 2 Hz, amatch can be identified when the UE transit data indicates a 1.2 Hzregular sinusoidal power generation pattern. In contrast for theexample, a match can be proscribed where the UE transit pattern is 1.2Hz but an irregular sinusoidal power generation pattern. The irregularsinusoidal nature can indicate another type of motion, e.g., foottapping or leg bouncing while seated, etc. One of skill in the art willappreciate that kinetic fingerprints can be inclusive or exclusive of awide number of characteristics and that all permutations thereof areconsidered to be within the scope of the present disclosure. Forexample, a kinetic fingerprint can consider a data source, e.g., model,type, brand, date of manufacture, aging or environmentalcharacteristics, etc., a data type, e.g., voltage, current, temporal,numeric, ratio, instant, historic, etc., a data acquisition window, dataacquisition environment, historic data, user preferences user defineddata, date reference frame(s), multiple data sources, etc.

TAC 210 can include radio selection modeling component 230. Radioselection modeling component 230 can model preferred radio selectionsfor one or more kinetic fingerprints. As such, given a kineticfingerprint (or a default fingerprint) radio selection modelingcomponent 230 can aid in designating one or more preferred radio (orradio technology) schema. As a non-limiting example, where a kineticfingerprint match for sitting at an office desk is indicated, radioselection modeling component 230 can indicate that a WiFi radio shouldbe on with a reselection scan every 5 minutes and a cellular radioshould be on with a reselection scan every 60 minutes. As a secondnon-limiting example, where a kinetic fingerprint match to bus travel isindicated, radio selection modeling component 230 can indicate that aWiFi radio should be turned off (presuming the bus does not have amobile WiFi system) and that a WAN radio should e turned on withreselection scanning every minute. Numerous other examples can readilybe appreciated but are omitted for brevity.

In an aspect, the models employed in radio selection modeling component230 can be of varying levels of complexity. As a non-limiting example, amodel for a stationary UE can indicate a first combination of radios. Asa second non-limiting example, a model for a stationary UE, at aparticular time of day, in a particular carrier network, can indicate asecond combination of radios. In another aspect, the models can behierarchical. As a non-limiting example, radio selection models can beselected initially for low or high-speed movement, then for a secondaryspeed indicator, then for a power consumption of radios, then forperformance of radios, them for carrier, then for cost, etc.

System 200 can further include radio selection component (RSC) 240. RSC240 can facilitate selection of preferred radios or radio technologiesas disclosed herein. RSC 240 can access a radio selection indicator,e.g., from TAC 210, and can correspondingly attempt to select theindicated radio(s). For example, where a WiFi radio is indicated aspreferential by TAC 210, RSC 240 can attempt to select the WiFi radio ofthe UE. Where the selection is not achieved, e.g., a user has manuallyturned off the WiFi radio, etc., TAC 210 can be signaled (notillustrated for clarity) and an alternate preferential radio can beselected accordingly.

System 200 can similarly include reselection interval component (RIC)250. RIC 250 can facilitate indication of a reselection interval. Areselection interval can be employed in generating a reselectionscanning schedule as disclosed in related application (U.S. Ser. No.12/624,643). In an aspect, reselection scanning can be adapted based onthe kinetic fingerprint and radio modeling performed by TAC 210.

FIG. 2 b is a block diagram of a system 260 employing a kineticfingerprint to select at least a radio technology or a reselectioninterval in accordance with aspects of the disclosed subject matter.System 260 can be the same as, or similar to, system 200. System 260 caninclude TAC 210, Kinetic fingerprint component 220, and radio selectionmodeling component 230 as disclosed herein. System 260 can furtherinclude assessment component 270, which can be the same as, or similarto, the one or more assessment components disclosed in relatedapplication (U.S. Ser. No. 12/624,643). Assessment component 270 caninclude RSC 272 which can be the same as, or similar to, RSC 240.Further, assessment component 270 can include RIC 274 which can be thesame as, or similar to, RIC 250. As will be appreciated by one of skillin the related arts, wherein assessment component 270 includes one orboth of RSC 272 or RIC 274, assessment component can facilitate accessto selection interval and/or radio selection information.

FIG. 3 is a block diagram of a system 300 for motion adaptive userequipment employing a kinetic sensor in accordance with aspectsdescribed herein. System 300 can be the same as, or similar to, system100 or 200. System 300 can include TAC 310, RSC 340 and RIC 350 whichcan be the same as, or similar to, the corresponding components ofsystem 100 or 200. Further system 200 can include kinetic sensorcomponent 335. Kinetic sensor component 335 can source UE transit data.In an aspect, kinetic sensor component 335 can facilitate access tokinetic changes for a UE including changes in speed, velocity, orposition as a function of time, historic kinetic data, kinetic datatransformed in to the frequency domain, etc. A non-limiting example ofkinetic sensor component 335 can be a five-axis capacitive accelerometerthat executes a fast Fourier transform (FFT) and stores frequency datain a local memory that is accessible by TAC 310. A second non-limitingexample of kinetic sensor component 335 can be a piezoelectric inertialsensor that sources a raw voltage measurement to TAC 310 (wherein TAC310 can separately access a temporal framework to facilitate deductionof a change in speed). One of skill in the art will appreciate thatnumerous kinetic sensors of varying levels of complexity can be employedas kinetic sensor component 335 without departing form the scope of thesubject disclosure. Further, it will be appreciated that any form ofdata, e.g., voltage, current, resistance, numerical, ratio, etc., can beemployed by TAC 310 within the scope of the present disclosure.

FIG. 4 is a block diagram of a system 400 for motion adaptive userequipment employing a kinetic generator in accordance with aspectsdescribed herein. System 400 can be the same as, or similar to, system100, 200, or 300. System 400 can include TAC 410, RSC 440 and RIC 450which can be the same as, or similar to, the corresponding components ofsystem 100, 200 or 300. System 400 can further include kinetic generatorcomponent 435. Kinetic generator component 435 can be the same as, orsimilar to, kinetic sensor component 335. Further, kinetic generatorcomponent 435 can include one or more kinetic sensors as sub-componentsof kinetic generator component 435.

In an aspect, kinetic generator component 435 can generate UE transitdata contemporaneously with kinetic power generation. For example, akinetic generator can generate power when it accelerates in a particulardirection. This same acceleration can be closely associated withmovement of the UE itself. As such, UE transit can be deduced ordetermined (or measured directly) from the output of a kineticgenerator. As a non-limiting example, a kinetic generator can functionas an accelerometer of sorts and, as such, three orthogonal kineticgenerators can be adapted to generate power from movements in 3-D space.These same movements in 3-D space can be deduced or determined bymonitoring the power generated in each axis. For example, movements inthe X-axis can be measured as a function of current generated form anX-axis kinetic generator. As a second example, a capacitive measurementcan be provided from the X-axis generator contemporaneously with thecurrent generated, which capacitive measurement can be associated withmovement in the X-direction as a function of time. One of skill in theart will appreciate that kinetic generators can provide the same, orsimilar, data as kinetic sensors with the added benefit of powergeneration. As such, a kinetic generator can offer an attractive optionfor accessing UE transit data with little or no negative effect on thebattery life (UE resources) of a UE.

FIG. 5 is a block diagram of a system 500 for motion adaptive userequipment employing frequency analysis technology in accordance withaspects described herein. System 500 can be the same as, or similar to,system 100, 200, 300, or 400. System 500 can include TAC 510, kineticgenerator 535, RSC 540 and RIC 550 which can be the same as, or similarto, the corresponding components of system 100, 200, 300 or 400. TAC 510can further include kinetic fingerprint component 520 which can be thesame as, or similar to, kinetic fingerprint component 220. Further,kinetic fingerprint component 520 can include frequency analysiscomponent 525.

Frequency analysis component 525 can facilitate conversion betweentemporal domain UE transit data and frequency domain UE transit data,e.g., converting frequency data into temporal data or the reverse byFFT, etc. In an aspect, this can be advantageous wherein particularmodes of UE transit can be strongly associated with highly periodickinetic changes. For example, rail travel can be associate with veryregular “bumps” as a train truck crosses over rail welds which aretypically at highly regular intervals. As another example, the gait of auser walking with a UE can be very regular and the rise and fall of thebody can be highly periodic. As a still further example, the highfrequency vibrations or a turbine engine, e.g., a jet engine, canproduce recognizable frequency patterns. As such, the frequency analysiscomponent 525 can be readily employed in kinetic fingerprinting asdisclosed herein.

FIG. 6 is a block diagram of a system 600 for motion adaptive userequipment employing learning technology in accordance with aspectsdescribed herein. System 600 can be the same as, or similar to, system100, 200, 300, 400 or 500. System 600 can include TAC 610, kineticgenerator 635, RSC 640 and RIC 650 which can be the same as, or similarto, the corresponding components of system 100, 200, 300, 400 or 500.TAC 610 can further include kinetic fingerprint component 620 that canbe the same as, or similar to, kinetic fingerprint component 220 or 520.Further, kinetic fingerprint component 620 can include learningcomponent 627. Learning component 627 can facilitate intelligentbehavior for TAC 610. In an aspect, learning component 627 can accessadditional data sources when UE transit data poorly matches the knownkinetic fingerprint (s). As an example, a user can have a vibratingmassage chair that can generate one or more sets of UE transit data thatmay not match any kinetic fingerprint of kinetic fingerprint component620. In response, default values can be communicated to RSC 640 or RIC650. Further, the response can trigger a learning mode in which, forexample, the user interface asks prompts the user to input informationrelating to the particular UE transit data for the massage chair. Thus,when the massage chair is encountered in the future, the UE TAC 610 canrespond appropriately. Numerous other examples of learning behavior arereadily appreciated and are not presented for conciseness.

System 600 can further include secondary motion related component 680communicatively coupled to learning component 627. Secondary motionrelated component 680 can include one or more secondary motion relatedsources. As such, when a learning opportunity occurs, learning component627 can access supplementary data sources to facilitate determinationsof preferential kinetic dependant behaviors, e.g., radio selection andreselection interval determination. These secondary sources can include,but are not limited to, user interface (UI) component 682, GPS component684, or mobility component 686. UI component 682 can facilitateinteraction with a user as a secondary data source, e.g., asking theuser to define one or more parameters related to the detected kineticdata. GPS component 684 can source global position data to augment theUE transit data. Mobility component 686 can be the same as, or similarto, a mobility component as disclosed in related application (U.S. Ser.No. 12/624,643). It will be readily appreciated that the learningfeature presently disclosed can facilitate rapid improvements in theperformance of system 600. In a further aspect, learned information canbe shared with other devices to improve their functionality, e.g.,common libraries, user profiles, data agglomeration, etc.

FIG. 7 is an exemplary flowchart of procedures defining a method 700 fordetermining at least a preferential radio technology parameter orreselection interval parameter in accordance with aspects describedherein. At 710, system 700 can access UE transit data. UE transit datacan be information related to the movement of a UE. For example, UE datacan be related to movement of a UE causing a kinetic generator togenerate power in a UE. At 720, the US transit data can be analyzed todetermine a kinetic class for the UE. The kinetic class can beassociated with one or more characteristics of the UE transit dataanalyzed. For example, analysis of the UE transit data can indicatefrequent acceleration and deceleration typically not exceeding 35 milesper hour (mph) and generally exceeding 15 mph. This can be classified as“city transit”, e.g., by bike, car, bus, etc. At 730, a preferred radiotechnology or reselection interval parameter can be determined based, atleast in part, on the UE kinetic class from 720. At this point method700 can end.

FIG. 8 is an exemplary flowchart of procedures defining a method 800 fordetermining at least a preferential radio technology parameter orreselection interval parameter in accordance with aspects describedherein. At 810, UE transit data can be accessed. At 820, the UE transitdata can be analyzed to, at least in part, determine a kineticfingerprint match for the UE transit data. Determinations of a kineticfingerprint can provide additional assumptions about the UE transitdata. For example, where a UE transit data set indicates speeds between15 and 35 mph with frequent acceleration and deceleration, pauses aftermoving right, followed by vibrations at the beginning and end of eachpause, e.g., from a door opening and closing, a fingerprint for a citybus can be matched (cf. to kinetic classification at 720). Where thecity bus match is made, other assumptions can be made, for example, thatthe bus can have a mobile WiFi connection, as opposed to a car or taxithat is less likely to have a WiFi connection. Where the WiFi connectioncan be a possibility, subsequent appropriate actions can be taken tocheck for, and take advantage of, said resource.

At 830, a kinetic class can be selected based, at least in part, on adetermined kinetic fingerprint from 820. The kinetic class can allow forsimplification of radio selection and reselection interval information.The kinetic classes can be as granular as the kinetic fingerprints,e.g., for each fingerprint there is a corresponding class, or can be ofhigher granularity, e.g., for every 10 fingerprints there is onecorresponding class, etc. At 840, a preferred radio technology orreselection interval parameter can be determined based, at least inpart, on the UE kinetic class from 830. At this point method 800 canend.

FIG. 9 is an exemplary flowchart of procedures defining a method 900 fordetermining at least a preferential radio technology parameter orreselection interval parameter in accordance with aspects describedherein. At 910, UE transit data can be accessed form a kineticgenerator. At 920 kinetic generator UE data can be transferred betweenthe temporal and frequency domain, e.g., by FFT, etc., as appropriate.At 930, a kinetic fingerprint can be determined for the UE transit data.Where a match cannot be positively determined, one or more defaultkinetic fingerprints can be employed. At 940, a kinetic class can beselected based in part on the kinetic fingerprint from 930.

At 950, a preferred radio technology or reselection interval parametercan be determined based, at least in part, on the UE kinetic class from940. At 960 a preferred radio technology (or radio) can be selected. At970, a preferred reselection interval can be selected. At this pointmethod 900 can end.

To provide further context for various aspects of the subjectspecification, FIG. 10 illustrates an example wireless communicationenvironment 1000, with associated components that can enable operationof a femtocell enterprise network in accordance with aspects describedherein. Wireless communication environment 1000 includes two wirelessnetwork platforms: (i) A macro network platform 1010 that serves, orfacilitates communication) with user equipment 1075 via a macro radioaccess network (RAN) 1070. It should be appreciated that in cellularwireless technologies, e.g., 4G, 3GPP UMTS, HSPA, 3GPP LTE, 3GPP UMB,macro network platform 1010 is embodied in a Core Network. (ii) A femtonetwork platform 1080, which can provide communication with UE 1075through a femto RAN 1090, linked to the femto network platform 1080through a routing platform 102 via backhaul pipe(s) 1085, whereinbackhaul pipe(s) are substantially the same a backhaul link 3853 below.It should be appreciated that femto network platform 1080 typicallyoffloads UE 1075 from macro network, once UE 1075 attaches, e.g.,through macro-to-femto handover, or via a scan of channel resources inidle mode, to femto RAN.

It is noted that RAN includes base station(s), or access point(s), andits associated electronic circuitry and deployment site(s), in additionto a wireless radio link operated in accordance with the basestation(s). Accordingly, macro RAN 1070 can comprise various coveragecells like cell 1205, while femto RAN 1090 can comprise multiple femtoaccess points. As mentioned above, it is to be appreciated thatdeployment density in femto RAN 1090 is substantially higher than inmacro RAN 1070.

Generally, both macro and femto network platforms 1010 and 1080 includecomponents, e.g., nodes, gateways, interfaces, servers, or platforms,that facilitate both packet-switched (PS), e.g., internet protocol (IP),frame relay, asynchronous transfer mode (ATM), and circuit-switched (CS)traffic, e.g., voice and data, and control generation for networkedwireless communication. In an aspect of the subject innovation, macronetwork platform 1010 includes CS gateway node(s) 1012 which caninterface CS traffic received from legacy networks like telephonynetwork(s) 1040, e.g., public switched telephone network (PSTN), orpublic land mobile network (PLMN), or a SS7 network 1060. Circuitswitched gateway 1012 can authorize and authenticate traffic, e.g.,voice, arising from such networks. Additionally, CS gateway 1012 canaccess mobility, or roaming, data generated through SS7 network 1060;for instance, mobility data stored in a VLR, which can reside in memory1030. Moreover, CS gateway node(s) 1012 interfaces CS-based traffic andsignaling and gateway node(s) 1018. As an example, in a 3GPP UMTSnetwork, gateway node(s) 1018 can be embodied in gateway GPRS supportnode(s) (GGSN).

In addition to receiving and processing CS-switched traffic andsignaling, gateway node(s) 1018 can authorize and authenticate PS-baseddata sessions with served, e.g., through macro RAN, wireless devices.Data sessions can include traffic exchange with networks external to themacro network platform 1010, like wide area network(s) (WANs) 1050; itshould be appreciated that local area network(s) (LANs) can also beinterfaced with macro network platform 1010 through gateway node(s)1018. Gateway node(s) 1018 generates packet data contexts when a datasession is established. To that end, in an aspect, gateway node(s) 1018can include a tunnel interface, e.g., tunnel termination gateway (TTG)in 3GPP UMTS network(s); not shown, which can facilitate packetizedcommunication with disparate wireless network(s), such as Wi-Finetworks. It should be further appreciated that the packetizedcommunication can include multiple flows that can be generated throughserver(s) 1014. It is to be noted that in 3GPP UMTS network(s), gatewaynode(s) 1018, e.g., GGSN, and tunnel interface, e.g., TTG, comprise apacket data gateway (PDG).

Macro network platform 1010 also includes serving node(s) 1016 thatconvey the various packetized flows of information or data streams,received through gateway node(s) 1018. As an example, in a 3GPP UMTSnetwork, serving node(s) can be embodied in serving GPRS support node(s)(SGSN).

As indicated above, server(s) 1014 in macro network platform 1010 canexecute numerous applications, e.g., location services, online gaming,wireless banking, wireless device management, etc., that generatemultiple disparate packetized data streams or flows, and manage, e.g.,schedule, queue, format, etc., such flows. Such application(s), forexample can include add-on features to standard services provided bymacro network platform 1010. Data streams can be conveyed to gatewaynode(s) 1018 for authorization/authentication and initiation of a datasession, and to serving node(s) 1016 for communication thereafter.Server(s) 1014 can also effect security, e.g., implement one or morefirewalls, of macro network platform 1010 to ensure network's operationand data integrity in addition to authorization and authenticationprocedures that CS gateway node(s) 1012 and gateway node(s) 1018 canenact. Moreover, server(s) 1014 can provision services from externalnetwork(s), e.g., WAN 1050, or Global Positioning System (GPS)network(s) (not shown). It is to be noted that server(s) 1014 caninclude one or more processor configured to confer at least in part thefunctionality of macro network platform 1010. To that end, the one ormore processor can execute code instructions stored in memory 1030, forexample.

In example wireless environment 1000, memory 1030 stores informationrelated to operation of macro network platform 1010. Information caninclude business data associated with subscribers; market plans andstrategies, e.g., promotional campaigns, business partnerships;operational data for mobile devices served through macro networkplatform; service and privacy policies; end-user service logs for lawenforcement; and so forth. Memory 1030 can also store information fromat least one of telephony network(s) 1040, WAN(s) 1050, or SS7 network1060, enterprise NW(s) 1065, or service NW(s) 1067.

Femto gateway node(s) 1084 have substantially the same functionality asPS gateway node(s) 1018. Additionally, femto gateway node(s) 1084 canalso include substantially all functionality of serving node(s) 1016. Inan aspect, femto gateway node(s) 1084 facilitates handover resolution,e.g., assessment and execution. Further, control node(s) 1020 canreceive handover requests and relay them to a handover component (notshown) via gateway node(s) 1084. According to an aspect, control node(s)1020 can support RNC capabilities.

Server(s) 1082 have substantially the same functionality as described inconnection with server(s) 1014. In an aspect, server(s) 1082 can executemultiple application(s) that provide service, e.g., voice and data, towireless devices served through femto RAN 1090. Server(s) 1082 can alsoprovide security features to femto network platform. In addition,server(s) 1082 can manage, e.g., schedule, queue, format, etc.,substantially all packetized flows, e.g., IP-based, frame relay-based,ATM-based, it generates in addition to data received from macro networkplatform 1010. It is to be noted that server(s) 1082 can include one ormore processor configured to confer at least in part the functionalityof macro network platform 1010. To that end, the one or more processorcan execute code instructions stored in memory 1086, for example.

Memory 1086 can include information relevant to operation of the variouscomponents of femto network platform 1080. For example operationalinformation that can be stored in memory 1086 can comprise, but is notlimited to, subscriber information; contracted services; maintenance andservice records; femto cell configuration, e.g., devices served throughfemto RAN 1090; access control lists, or white lists; service policiesand specifications; privacy policies; add-on features; and so forth.

It is noted that femto network platform 1080 and macro network platform1010 can be functionally connected through one or more reference link(s)or reference interface(s). In addition, femto network platform 1080 canbe functionally coupled directly (not illustrated) to one or more ofexternal network(s) 1040, 1050, 1060, 1065 or 1067. Reference link(s) orinterface(s) can functionally link at least one of gateway node(s) 1084or server(s) 1086 to the one or more external networks 1040, 1050, 1060,1065 or 1067.

FIG. 11 illustrates a wireless environment that includes macro cells andfemtocells for wireless coverage in accordance with aspects describedherein. In wireless environment 1150, two areas 1105 represent “macro”cell coverage; each macro cell is served by a base station 1110. It canbe appreciated that macro cell coverage area 1105 and base station 1110can include functionality, as more fully described herein, for example,with regard to system 1100. Macro coverage is generally intended toserve mobile wireless devices, like UE 1120 _(A), 1120 _(B), in outdoorslocations. An over-the-air wireless link 115 provides such coverage, thewireless link 1215 comprises a downlink (DL) and an uplink (UL), andutilizes a predetermined band, licensed or unlicensed, of the radiofrequency (RF) spectrum. As an example, UE 1120 _(A), 1120 _(E) can be a3GPP Universal Mobile Telecommunication System (UMTS) mobile phone. Itis noted that a set of base stations, its associated electronics,circuitry or components, base stations control component(s), andwireless links operated in accordance to respective base stations in theset of base stations form a radio access network (RAN). In addition,base station 1110 communicates via backhaul link(s) 1151 with a macronetwork platform 1160, which in cellular wireless technologies, e.g.,3rd Generation Partnership Project (3GPP) Universal MobileTelecommunication System (UMTS), Global System for Mobile Communication(GSM), represents a core network.

In an aspect, macro network platform 1160 controls a set of basestations 1110 that serve either respective cells or a number of sectorswithin such cells. Base station 1110 comprises radio equipment 1114 foroperation in one or more radio technologies, and a set of antennas 1112,e.g., smart antennas, microwave antennas, satellite dish(es), etc., thatcan serve one or more sectors within a macro cell 1105. It is noted thata set of radio network control node(s), which can be a part of macronetwork platform; a set of base stations, e.g., Node B 1110, that servea set of macro cells 1105; electronics, circuitry or componentsassociated with the base stations in the set of base stations; a set ofrespective OTA wireless links, e.g., links 1115 or 1116, operated inaccordance to a radio technology through the base stations; and backhaullink(s) 1155 and 1151 form a macro radio access network (RAN). Macronetwork platform 1160 also communicates with other base stations (notshown) that serve other cells (not shown). Backhaul link(s) 1151 or 1153can include a wired backbone link, e.g., optical fiber backbone,twisted-pair line, T1/E1 phone line, a digital subscriber line (DSL)either synchronous or asynchronous, an asymmetric ADSL, or a coaxialcable, etc., or a wireless, e.g., line-of-sight (LOS) or non-LOS,backbone link. Backhaul pipe(s) 1155 link disparate base stations 1110.According to an aspect, backhaul link 1153 can connect multiple femtoaccess points 1130 and/or controller components (CC) 1101 to the femtonetwork platform 1102. In one example, multiple femto APs can beconnected to a routing platform (RP) 1087, which in turn can be connectto a controller component (CC) 1101. Typically, the information from UEs1120 _(A) can be routed by the RP 102, for example, internally, toanother UE 1120 _(A) connected to a disparate femto AP connected to theRP 1087, or, externally, to the femto network platform 1102 via the CC1101.

In wireless environment 1150, within one or more macro cell(s) 1105, aset of femtocells 1145 served by respective femto access points (APs)1130 can be deployed. It can be appreciated that, aspects of the subjectinnovation are geared to femtocell deployments with substantive femto APdensity, e.g., 10⁴-10⁷ femto APs 1130 per base station 1110. Accordingto an aspect, a set of femto access points 1130 ₁-3730 _(N), with N anatural number, can be functionally connected to a routing platform1087, which can be functionally coupled to a controller component 1101.The controller component 1101 can be operationally linked to the femtonetwork platform 330 by employing backhaul link(s) 1153. Accordingly,UEs UE 3720 _(A) connected to femto APs 1130 ₁-3830 _(N) can communicateinternally within the femto enterprise via the routing platform (RP)1087 and/or can also communicate with the femto network platform 1102via the RP 1087, controller component 1101 and the backhaul link(s)1153. It can be appreciated that although only one femto enterprise isdepicted in FIG. 11, multiple femto enterprise networks can be deployedwithin a macro cell 1105.

It is noted that while various aspects, features, or advantagesdescribed herein have been illustrated through femto access point(s) andassociated femto coverage, such aspects and features also can beexploited for home access point(s) (HAPs) that provide wireless coveragethrough substantially any, or any, disparate telecommunicationtechnologies, such as for example Wi-Fi (wireless fidelity) or picocelltelecommunication. Additionally, aspects, features, or advantages of thesubject innovation can be exploited in substantially any wirelesstelecommunication, or radio, technology; for example, Wi-Fi, WorldwideInteroperability for Microwave Access (WiMAX), Enhanced General PacketRadio Service (Enhanced GPRS), 3GPP LTE, 3GPP2 UMB, 3GPP UMTS, HSPA,HSDPA, HSUPA, or LTE Advanced. Moreover, substantially all aspects ofthe subject innovation can include legacy telecommunicationtechnologies.

Referring now to FIG. 12, there is illustrated a block diagram of anexemplary computer system operable to execute the disclosedarchitecture. In order to provide additional context for various aspectsof the disclosed subject matter, FIG. 12 and the following discussionare intended to provide a brief, general description of a suitablecomputing environment 1200 in which the various aspects of the disclosedsubject matter can be implemented. Additionally, while the disclosedsubject matter described above may be suitable for application in thegeneral context of computer-executable instructions that may run on oneor more computers, those skilled in the art will recognize that thedisclosed subject matter also can be implemented in combination withother program modules and/or as a combination of hardware and software.

Generally, program modules include routines, programs, components, datastructures, etc., that perform particular tasks or implement particularabstract data types. Moreover, those skilled in the art will appreciatethat the inventive methods can be practiced with other computer systemconfigurations, including single-processor or multiprocessor computersystems, minicomputers, mainframe computers, as well as personalcomputers, hand-held computing devices, microprocessor-based orprogrammable consumer electronics, and the like, each of which can beoperatively coupled to one or more associated devices.

The illustrated aspects of the disclosed subject matter may also bepracticed in distributed computing environments where certain tasks areperformed by remote processing devices that are linked through acommunications network. In a distributed computing environment, programmodules can be located in both local and remote memory storage devices.As a non-limiting example, kinetic fingerprint component 520 can belocated in the cloud or in the UE. As a further non-limiting example,the various sub-components of secondary motion related component 680 canbe embodied on the UE, in the cloud, on a user PC, or combinationsthereof, etc.

Computing devices typically include a variety of media, which caninclude computer-readable storage media and/or communications media,which two terms are used herein differently from one another as follows.Computer-readable storage media can be any available storage media thatcan be accessed by the computer and includes both volatile andnonvolatile media, removable and non-removable media. By way of example,and not limitation, computer-readable storage media can be implementedin connection with any method or technology for storage of informationsuch as computer-readable instructions, program modules, structureddata, or unstructured data. Computer-readable storage media can include,but are not limited to, RAM, ROM, EEPROM, flash memory or other memorytechnology, CD ROM, digital versatile disk (DVD) or other optical diskstorage, magnetic cassettes, magnetic tape, magnetic disk storage orother magnetic storage devices, or other tangible and/or non-transitorymedia which can be used to store desired information. Computer-readablestorage media can be accessed by one or more local or remote computingdevices, e.g., via access requests, queries or other data retrievalprotocols, for a variety of operations with respect to the informationstored by the medium.

Communications media typically embody computer-readable instructions,data structures, program modules or other structured or unstructureddata in a data signal such as a modulated data signal, e.g., a carrierwave or other transport mechanism, and include any information deliveryor transport media. The term “modulated data signal” or signals refersto a signal that has one or more of its characteristics set or changedin such a manner as to encode information in one or more signals. By wayof example, and not limitation, communication media include wired media,such as a wired network or direct-wired connection, and wireless mediasuch as acoustic, RF, infrared and other wireless media.

With reference again to FIG. 12, the exemplary environment 1200 forimplementing various aspects of the disclosed subject matter includes acomputer 1202, the computer 1202 including a processing unit 1204, asystem memory 1206 and a system bus 1208. The system bus 1208 couples tosystem components including, but not limited to, the system memory 1206to the processing unit 1204. The processing unit 1204 can be any ofvarious commercially available processors. Dual microprocessors andother multi-processor architectures may also be employed as theprocessing unit 1204.

The system bus 1208 can be any of several types of bus structure thatmay further interconnect to a memory bus (with or without a memorycontroller), a peripheral bus, and a local bus using any of a variety ofcommercially available bus architectures. The system memory 1206includes read-only memory (ROM) 1210 and random access memory (RAM)1212. A basic input/output system (BIOS) is stored in a non-volatilememory 1210 such as ROM, EPROM, EEPROM, which BIOS contains the basicroutines that help to transfer information between elements within thecomputer 1202, such as during start-up. The RAM 1212 can also include ahigh-speed RAM such as static RAM for caching data.

The computer 1202 further includes an internal hard disk drive (HDD)1214, e.g., EIDE, SATA, which internal hard disk drive 1214 may also beconfigured for external use in a suitable chassis, e.g., 1215, amagnetic floppy disk drive (FDD) 1216, e.g., to read from or write to aremovable diskette 1218, and an optical disk drive 1220, e.g., reading aCD-ROM disk 1222 or, to read from or write to other high capacityoptical media such as the DVD. The hard disk drive 1214 (or 1215),magnetic disk drive 1216 and optical disk drive 1220 can be connected tothe system bus 1208 by a hard disk drive interface 1224, a magnetic diskdrive interface 1226 and an optical drive interface 1228, respectively.The interface 1224 for external drive implementations includes at leastone or both of Universal Serial Bus (USB) and IEEE1394 interfacetechnologies. Other external drive connection technologies are withincontemplation of the subject matter disclosed herein.

The drives and their associated computer-readable media providenonvolatile storage of data, data structures, computer-executableinstructions, and so forth. For the computer 1202, the drives and mediaaccommodate the storage of any data in a suitable digital format.Although the description of computer-readable media above refers to aHDD, a removable magnetic diskette, and a removable optical media suchas a CD or DVD, it should be appreciated by those skilled in the artthat other types of media which are readable by a computer, such as zipdrives, magnetic cassettes, flash memory cards, cartridges, and thelike, may also be used in the exemplary operating environment, andfurther, that any such media may contain computer-executableinstructions for performing the methods of the disclosed subject matter.

A number of program modules can be stored in the drives and RAM 1212,including an operating system 1230, one or more application programs1232, other program modules 1234 and program data 1236. All or portionsof the operating system, applications, modules, and/or data can also becached in the RAM 1212. It is appreciated that the disclosed subjectmatter can be implemented with various commercially available operatingsystems or combinations of operating systems.

A user can enter commands and information into the computer 1202 throughone or more wired/wireless input devices, e.g., a keyboard 1238 and apointing device, such as a mouse 1240. Other input devices (not shown)may include a microphone, an IR remote control, a joystick, a game pad,a stylus pen, touch screen, or the like. These and other input devicesare often connected to the processing unit 1204 through an input deviceinterface 1242 that is coupled to the system bus 1208, but can beconnected by other interfaces, such as a parallel port, an IEEE1394serial port, a game port, a USB port, an IR interface, etc.

A monitor 1244 or other type of display device is also connected to thesystem bus 1208 via an interface, such as a video adapter 1246. Inaddition to the monitor 1244, a computer typically includes otherperipheral output devices (not shown), such as speakers, printers, etc.

The computer 1202 may operate in a networked environment using logicalconnections via wired and/or wireless communications to one or moreremote computers, such as a remote computer(s) 1248. The remotecomputer(s) 1248 can be a workstation, a server computer, a router, apersonal computer, a mobile device, portable computer,microprocessor-based entertainment appliance, a peer device or othercommon network node, and typically includes many or all of the elementsdescribed relative to the computer 1202, although, for purposes ofbrevity, only a memory/storage device 1250 is illustrated. The logicalconnections depicted include wired/wireless connectivity to a local areanetwork (LAN) 1252 and/or larger networks, e.g., a wide area network(WAN) 1254. Such LAN and WAN networking environments are commonplace inoffices and companies, and facilitate enterprise-wide computer networks,such as intranets, all of which may connect to a global communicationsnetwork, e.g., the Internet.

When used in a LAN networking environment, the computer 1202 isconnected to the local network 1252 through a wired and/or wirelesscommunication network interface or adapter 1256. The adapter 1256 mayfacilitate wired or wireless communication to the LAN 1252, which mayalso include a wireless access point disposed thereon for communicatingwith the wireless adapter 1256.

When used in a WAN networking environment, the computer 1202 can includea modem 1258, or is connected to a communications server on the WAN1254, or has other means for establishing communications over the WAN1254, such as by way of the Internet. The modem 1258, which can beinternal or external and a wired or wireless device, is connected to thesystem bus 1208 via the serial port interface 1242. In a networkedenvironment, program modules depicted relative to the computer 1202, orportions thereof, can be stored in the remote memory/storage device1250. It will be appreciated that the network connections shown areexemplary and other means of establishing a communications link betweenthe computers can be used.

The computer 1202 is operable to communicate with any wireless devicesor entities operatively disposed in wireless communication, e.g., aprinter, scanner, desktop and/or portable computer, portable dataassistant, communications satellite, any piece of equipment or locationassociated with a wirelessly detectable tag, e.g., a kiosk, news stand,restroom, etc., and telephone. This includes at least Wi-Fi andBluetooth™ wireless technologies. Thus, the communication can be apredefined structure as with a conventional network or simply an ad hoccommunication between at least two devices.

Wi-Fi, or Wireless Fidelity, allows connection to the Internet from acouch at home, a bed in a hotel room, or a conference room at work,without wires. Wi-Fi is a wireless technology similar to that used in acell phone that enables such devices, e.g., computers, to send andreceive data indoors and out; anywhere within the range of a basestation. Wi-Fi networks use radio technologies called IEEE802.11(a, b,g, n, etc.) to provide secure, reliable, fast wireless connectivity. AWi-Fi network can be used to connect computers to each other, to theInternet, and to wired networks (which use IEEE802.3 or Ethernet). Wi-Finetworks operate in the unlicensed 2.4 and 5 GHz radio bands, at an 11Mbps (802.11b) or 54 Mbps (802.11a) data rate, for example, or withproducts that contain both bands (dual band), so the networks canprovide real-world performance similar to the basic “10BaseT” wiredEthernet networks used in many offices.

Various aspects or features described herein can be implemented as amethod, apparatus, or article of manufacture using standard programmingand/or engineering techniques. In addition, various aspects disclosed inthe subject specification can also be implemented through programmodules stored in a memory and executed by a processor, or othercombination of hardware and software, or hardware and firmware. The term“article of manufacture” as used herein is intended to encompass acomputer program accessible from any computer-readable device, carrier,or media. For example, computer readable media can include but are notlimited to magnetic storage devices, e.g., hard disk, floppy disk,magnetic strips, etc., optical disks, e.g., compact disc (CD), digitalversatile disc (DVD), blu-ray disc (BD), etc., smart cards, and flashmemory devices, e.g., card, stick, key drive, etc. Additionally itshould be appreciated that a carrier wave can be employed to carrycomputer-readable electronic data such as those used in transmitting andreceiving electronic mail or in accessing a network such as the internetor a local area network (LAN). Of course, those skilled in the art willrecognize many modifications may be made to this configuration withoutdeparting from the scope or spirit of the disclosed subject matter.

As it employed in the subject specification, the term “processor” canrefer to substantially any computing processing unit or devicecomprising, but not limited to comprising, single-core processors;single-processors with software multithread execution capability;multi-core processors; multi-core processors with software multithreadexecution capability; multi-core processors with hardware multithreadtechnology; parallel platforms; and parallel platforms with distributedshared memory. Additionally, a processor can refer to an integratedcircuit, an application specific integrated circuit (ASIC), a digitalsignal processor (DSP), a field programmable gate array (FPGA), aprogrammable logic controller (PLC), a complex programmable logic device(CPLD), a discrete gate or transistor logic, discrete hardwarecomponents, or any combination thereof designed to perform the functionsdescribed herein. Processors can exploit nano-scale architectures suchas, but not limited to, molecular and quantum-dot based transistors,switches and gates, in order to optimize space usage or enhanceperformance of user equipment. A processor also can be implemented as acombination of computing processing units.

In the subject specification, terms such as “store,” “data store,” “datastorage,” “database,” “repository,” and substantially any otherinformation storage component relevant to operation and functionality ofa component, refer to “memory components,” or entities embodied in a“memory” or components comprising the memory. It will be appreciatedthat the memory components described herein can be either volatilememory or nonvolatile memory, or can include both volatile andnonvolatile memory. In addition, memory components or memory elementscan be removable or stationary. Moreover, memory can be internal orexternal to a device or component, or removable or stationary. Memorycan include various types of media that are readable by a computer, suchas hard-disc drives, zip drives, magnetic cassettes, flash memory cardsor other types of memory cards, cartridges, or the like.

By way of illustration, and not limitation, nonvolatile memory caninclude read only memory (ROM), programmable ROM (PROM), electricallyprogrammable ROM (EPROM), electrically erasable ROM (EEPROM), or flashmemory. Volatile memory can include random access memory (RAM), whichacts as external cache memory. By way of illustration and notlimitation, RAM is available in many forms such as synchronous RAM(SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rateSDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), anddirect Rambus RAM (DRRAM). Additionally, the disclosed memory componentsof systems or methods herein are intended to comprise, without beinglimited to comprising, these and any other suitable types of memory.

What has been described above includes examples of the variousembodiments. It is, of course, not possible to describe everyconceivable combination of components or methodologies for purposes ofdescribing the embodiments, but one of ordinary skill in the art mayrecognize that many further combinations and permutations are possible.Accordingly, the detailed description is intended to embrace all suchalterations, modifications, and variations that fall within the spiritand scope of the appended claims.

In particular and in regard to the various functions performed by theabove described components, devices, circuits, systems and the like, theterms (including a reference to a “means”) used to describe suchcomponents are intended to correspond, unless otherwise indicated, toany component which performs the specified function of the describedcomponent, e.g., a functional equivalent, even though not structurallyequivalent to the disclosed structure, which performs the function inthe herein illustrated exemplary aspects of the embodiments. In thisregard, it will also be recognized that the embodiments includes asystem as well as a computer-readable medium having computer-executableinstructions for performing the acts and/or events of the variousmethods.

In addition, while a particular feature may have been disclosed withrespect to only one of several implementations, such feature may becombined with one or more other features of the other implementations asmay be desired and advantageous for any given or particular application.Furthermore, to the extent that the terms “includes,” and “including”and variants thereof are used in either the detailed description or theclaims, these terms are intended to be inclusive in a manner similar tothe term “comprising.”

What is claimed is:
 1. A system, comprising: a memory to storeinstructions; and a processor, coupled to the memory, that facilitatesexecution of the instructions to perform operations, comprising:receiving user equipment power information based on power generated froma movement of a kinetic generator of a user equipment; determining apower fluctuation pattern based on the user equipment power information;receiving data representing a kinetic pattern comprising a predeterminedpower fluctuation characteristic corresponding to a kinetic generatormovement of a kinetic generator engaged in a defined user equipmenttransit mode; determining a level of probability based on a correlationdetermined between the kinetic pattern and the power fluctuationpattern, wherein the level of probability is indicative of a probabilitythat the user equipment is engaged in the defined user equipment transitmode of the kinetic pattern; and determining radio selectioninformation, based on the level of probability, to facilitate selectionof a performance property of a radio of the user equipment.
 2. Thesystem of claim 1, wherein the operations further comprise: determiningradio reselection interval information of a user equipment radio basedon the radio selection information.
 3. The system of claim 1, whereinthe receiving the user equipment power information comprises receivingthe user equipment power information based on voltage generated from themovement of the kinetic generator of the user equipment.
 4. The systemof claim 1, wherein the receiving the user equipment power informationcomprises receiving the user equipment power information based oncurrent generated from the movement of the kinetic generator of the userequipment.
 5. The system of claim 1, wherein the determining the powerfluctuation pattern comprises determining a characteristic of the powerfluctuation pattern based on a transformation of a portion of the userequipment power information between a time domain and a frequencydomain.
 6. The system of claim 5, wherein the transformation comprisesapplication of a fast Fourier transform function.
 7. The system of claim1, wherein the determining the level of probability comprises detectinga set of predetermined power fluctuation characteristics for the defineduser equipment transit mode, comprising the predetermined powerfluctuation characteristic, wherein the probability of the userequipment being engaged in the defined user equipment transit mode ofthe kinetic pattern is based on a correlation determined between thekinetic pattern and the set of predetermined power fluctuationcharacteristics.
 8. The system of claim 7, wherein the determining thelevel of probability comprises applying a weighting factor to apredetermined power fluctuation characteristic of the set ofpredetermined power fluctuation characteristics.
 9. The system of claim8, wherein the applying the weighting factor comprises increasing aneffect of the set of predetermined power fluctuation characteristics indetermining the level of probability.
 10. The system of claim 8, whereinthe applying the weighting factor comprises decreasing an effect of theset of predetermined power fluctuation characteristics in determiningthe level of probability.
 11. The system of claim 1, wherein thedetermining the power fluctuation pattern comprises filtering the userequipment power information.
 12. The system of claim 11, wherein thefiltering the user equipment power information comprises reducing amagnitude of a power fluctuation characteristic of the power fluctuationpattern.
 13. The system of claim 12, wherein the filtering the userequipment power information comprises reducing the magnitude of thepower fluctuation characteristic if the power fluctuation characteristicdoes not satisfy a rule relating to the power fluctuation pattern. 14.The system of claim 1, wherein the kinetic pattern is generated from amodel of the kinetic generator engaged in the defined user equipmenttransit mode.
 15. The system of claim 1, wherein the kinetic pattern isgenerated from another kinetic generator of another user equipmentpreviously engaged in the defined user equipment transit mode.
 16. Thesystem of claim 1, wherein the kinetic pattern is generated from thekinetic generator of the user equipment previously engaged in thedefined user equipment transit mode.
 17. A method, comprising:receiving, by a system comprising a processor, user equipment powerinformation based on power generated from a movement of a kinetic sensorof a user equipment; determining, by the system, a power fluctuationpattern based on the user equipment power information; receiving, by thesystem, a kinetic pattern comprising a predetermined power fluctuationcharacteristic corresponding to a kinetic sensor movement of a kineticsensor engaged in a defined user equipment transit mode; determining, bythe system, a level of probability based on a correlation determinedbetween the kinetic pattern and the power fluctuation pattern, whereinthe level of probability is indicative of a probability that the userequipment is engaged in the defined user equipment transit mode of thekinetic pattern; and determining, by the system, radio selectioninformation, based on the level of probability, to facilitate selectionof a performance property of a radio of the user equipment.
 18. Themethod of claim 17, further comprising: receiving confirmation, frominput to a user interface of the user equipment, of a determined userequipment transit mode, wherein the defined user equipment transit modeis based on the level of probability.
 19. A computer-readable storagedevice storing instructions that, in response to execution, cause asystem comprising a processor to perform operations, comprising:receiving frequency information based on signals generated from amovement of a kinetic sensor of a user equipment; determining afluctuation pattern based on the frequency information; receiving akinetic pattern comprising a predetermined frequency characteristiccorresponding to a kinetic sensor movement of a kinetic sensor engagedin a defined transit mode of the user equipment; determining a level ofprobability based on a correlation determined between the kineticpattern and the fluctuation pattern, wherein the level of probability isindicative of a probability that the user equipment is engaged in thedefined transit mode of the kinetic pattern; and determining radioselection information, based on the level of probability, to facilitateselection of a property of a radio of the user equipment.
 20. Thecomputer-readable storage device of claim 19, wherein the determiningthe fluctuation pattern comprises selectively filtering the frequencyinformation.